Automatic Target Recognition For the TOPCAT System

Abstract

We have developed a proposed sensor system for the TOPCAT anti-armor system. It analyzes cross-sectional measurements of the underlying terrain, detecting targets by their distinctive shape. Sparsely-sampled point from a single scan line are fed as input to a Parzen estimator, which makes the target/ no-target decision. Morphological operators then remove spurious noise points, producing large blobs over the detected target region. Results are shown, using the GTVISIT simulation system to produce test data. ATR, Automatic target recognition, TOPCAT, Statistical pattern recognition, Parzen classifier.

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Document Details

Document Type
Technical Report
Publication Date
Jan 15, 1993
Accession Number
ADA260430

Entities

People

  • A. C. Kak
  • R. L. Cromwell

Organizations

  • Purdue University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Armored Vehicles
  • Automatic
  • Classification
  • Compressed Sensing
  • Detection
  • Detectors
  • Kernel Functions
  • Machine Learning
  • Measurement
  • Military Research
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Recognition
  • Signal Processing
  • Target Recognition

Readers

  • Aerospace Research.
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference